This analysis explores relationships between indicators across
countries such as percentage of agricultural land, CO2 emissions per
capita, and size of surface area using World Bank data. It is divided
into two main parts, with this script focusing on the second question.
For further observation of the first question, refer to the file
‘Analysis/agriculture.Rmd’.
1. Is there a relationship between
the percentage of agricultural land and CO2 emissions per capita across
countries?
2. Does the size of the surface
area of the country play a role?
One further aspect that might change the non-relationship recorded in
the ‘agriculture.Rmd’ file is the introduction of another variable to
take into account, namely the countries’ surface areas.
Starting with the initial comparison between the variables within the
ranges of the data observed, we get the following first overview.
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 180 243610 796100 2461119 1285220 17098250
As we can see, there are several countries with no changes in
surface area throughout the interested time span at all. Therefore,
before heading forward, we first want to zoom in a little closer on
those with changes.
## Anzahl der Länder ohne Veränderungen: 10
For the vast majority of the countries, the changes can be
classified as under 1000 square kilometers over the whole time span.
Similar insights can be derived when looking at the relative
changes.
For each country, even those with changes throughout the time span,
there are at most marginal changes of two percent in surface area. To
finally confirm those claims, we take a look at the scatter
decomposition.
## Streuung zwischen den Ländern: 1.783129e+13
In conclusion, we recognize that the changes in surface area are
negligible over time. Therefore, we drop our focus on the development
over time considering this variable when moving on. More interesting
might be shifting the perspective towards whether the absolute amount of
surface area has any influence on the relationship between agricultural
land and CO2 emissions for the observed countries.
For this
exploration, we want to distinguish our countries into the following
groups:
We see there is no direct influence obvious through the grouping of
the data. Let’s dig deeper by looking at the time-specific distribution.
The biggest anomalies regarding the CO2 emissions with the
percentage of agricultural land in mind seem to be the moderate and very
large surface area countries. Here on one hand, we can detect comparably
high percentages in agricultural land for the moderate area countries,
but those do not transfer themselves to any obvious differences in the
CO2 emissions compared to the other groups. On the other hand, the very
large countries stand out by having the supposedly expectable highest
CO2 emissions among all groups. Marginal differences appear between the
development over time, as the very large area countries are constant
over the two decade timespan, while the other groups have slightly
increasing trends.
If we finally pivot back to our normalized
comparison we did earlier, we can do the same now with our grouped data
according to the surface area categories.
We cannot identify any obvious connection between the CO2
emissions per capita and the percentage of agricultural land even with
the interested countries categorized by surface area.